Effects of Prosthesis Mass on Hip Energetics, Prosthetic Knee Torque, and Prosthetic Knee Stiffness and Damping Parameters Required for Transfemoral Amputees to Walk With Normative Kinematics

We quantify how the hip energetics and knee torque required for an above-knee prosthesis user to walk with the kinematics of able-bodied humans vary with the inertial properties of the prosthesis. We also select and optimize passive mechanical components for a prosthetic knee to accurately reproduce the required knee torque. Previous theoretical studies have typically investigated the effects of prosthesis inertial properties on energetic parameters by modifying both mass and mass distribution of the prosthesis and computing kinetic and energetic parameters only during swing. Using inverse dynamics, we determined the effects of independently modifying mass and mass distribution of the prosthesis, and we computed parameters during both stance and swing. Results showed that reducing prosthesis mass significantly affected hip energetics, whereas reducing mass distribution did not. Reducing prosthesis mass to 25% of the mass of a physiological leg decreased peak stance hip power by 26%, average swing hip power by 74%, and absolute hip work over the gait cycle by 22%. Previous studies have also typically optimized prosthetic knee components to reproduce the knee torque generated by able-bodied humans walking with normative kinematics. However, because the prosthetic leg of an above-knee prosthesis user weighs significantly less than a physiological leg, the knee torque required for above-knee prosthesis users to walk with these kinematics may be significantly different. Again using inverse dynamics, it was found that changes in prosthesis mass and mass distribution significantly affected this required torque. Reducing the mass of the prosthesis to 25% of the mass of the physiological leg increased peak stance torque by 43% and decreased peak swing torque by 76%. The knee power required for an above-knee prosthesis user to walk with the kinematics of able-bodied humans was analyzed to select passive mechanical components for the prosthetic knee. The coefficients of the components were then optimized to replicate the torque required to walk with the kinematics of able-bodied humans. A prosthetic knee containing a single linear spring and two constant-force dampers was found to accurately replicate the targeted torque (R[superscript 2]=0.90 for a typical prosthesis). Optimal spring coefficients were found to be relatively insensitive to mass alterations of the prosthetic leg, but optimal damping coefficients were sensitive. In particular, as the masses of the segments of the prosthetic leg were altered between 25% and 100% of able-bodied values, the optimal damping coefficient of the second damper varied by 330%, with foot mass alterations having the greatest effect on its value.MIT Department of Physics Pappalardo Program (Fellowship)MIT Public Service Center FellowshipNational Science Foundation (U.S.). Graduate Research Fellowship (1122374)MIT Tata Center for Technology and Desig

Identification of design requirements for a high-performance, low-cost, passive prosthetic knee through user analysis and dynamic simulation

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2013.Cataloged from PDF version of thesis.Includes bibliographical references.In January 2012, a partnership was initiated between the Massachusetts Institute of Technology and Bhagwan Mahaveer Viklang Sahayata Samiti (BMVSS, a.k.a., Jaipur Foot) to design a high-performance, low-cost, passive prosthetic knee for transfemoral amputees in India. The knee was primarily intended to improve the walking gait of amputees relative to existing low-cost devices. This thesis aimed to identify detailed design requirements for the prosthetic knee through user analysis and dynamic simulation. User analysis identified the needs and constraints of numerous stakeholders in the prosthesis development process. Members of the Indian biomechanics, prosthetics, and rehabilitation communities were interviewed to identify general requirements for the design, manufacturing, evaluation, and fitting of a prosthetic knee, and a structured survey of Indian amputees was conducted to quantify the demographics, functional capabilities, and functional needs of future end users. Dynamic simulation identified methods to enable transfemoral amputees to walk with reduced energy expenditure and normative gait kinematics. 2-dimensional inverse dynamics simulations were used to calculate the effects of inertial alterations of a prosthetic leg on the energy expenditure required to walk with normative kinematics. In addition, simulations were performed to compute the effects of inertial alterations on the knee moment required to walk with normative kinematics. Mechanical power analysis, sensitivity analysis, and optimization were used to formulate a passive mechanical model that could accurately reproduce the specified knee moment. The effects of walking cadence on critical results were also examined. Through the identification of user-centered and biomechanical requirements, the thesis provides a blueprint for the mechanism design comprising the next phase of the project.by Yashraj S. Narang.S.M

The Effects of Prosthesis Inertial Properties on Prosthetic Knee Moment and Hip Energetics Required to Achieve Able-bodied Kinematics

There is a major need in the developing world for a low-cost prosthetic knee that enables users to walk with able-bodied kinematics and low energy expenditure. To efficiently design such a knee, the relationship between the inertial properties of a prosthetic leg and joint kinetics and energetics must be determined. In this paper, using inverse dynamics, the theoretical effects of varying the inertial properties of an above-knee prosthesis on the prosthetic knee moment, hip power, and absolute hip work required for walking with ablebodied kinematics were quantified. The effects of independently varying mass and moment of inertia of the prosthesis, as well as independently varying the masses of each prosthesis segment, were also compared. Decreasing prosthesis mass to 25% of physiological leg mass increased peak late-stance knee moment by 43% and decreased peak swing knee moment by 76%. In addition, it reduced peak stance hip power by 26%, average swing hip power by 76%, and absolute hip work by 22%. Decreasing upper leg mass to 25% of its physiological value reduced absolute hip work by just 2%, whereas decreasing lower leg and foot mass reduced work by up to 22%, with foot mass having the greater effect. Results are reported in the form of parametric illustrations that can be utilized by researchers, designers, and prosthetists. The methods and outcomes presented have the potential to improve prosthetic knee component selection, facilitate ablebodied kinematics, and reduce energy expenditure for users of low-cost, passive knees in developing countries, as well as for users of advanced active knees in developed countries.MIT Department of Physics Pappalardo Program (Fellowship)Massachusetts Institute of Technology. Public Service CenterMassachusetts Institute of Technology. Research Support CommitteeNational Science Foundation (U.S.). Graduate Research Fellowship (Grant 1122374)MIT Tata Center for Technology and Desig

The Effects of the Inertial Properties of Above-Knee Prostheses on Optimal Stiffness, Damping, and Engagement Parameters of Passive Prosthetic Knees

Our research aims to design low-cost, high-performance, passive prosthetic knees for developing countries. In this study, we determine optimal stiffness, damping, and engagement parameters for a low-cost, passive prosthetic knee that consists of simple mechanical elements and may enable users to walk with the normative kinematics of able-bodied humans. Knee joint power was analyzed to divide gait into energy-based phases and select mechanical components for each phase. The behavior of each component was described with a polynomial function, and the coefficients and polynomial order of each function were optimized to reproduce the knee moments required for normative kinematics of able-bodied humans. Sensitivity of coefficients to prosthesis mass was also investigated. The knee moments required for prosthesis users to walk with able-bodied normative kinematics were accurately reproduced with a mechanical system consisting of a linear spring, two constant-friction dampers, and three clutches (R[superscript 2]=0.90 for a typical prosthetic leg). Alterations in upper leg, lower leg, and foot mass had a large influence on optimal coefficients, changing damping coefficients by up to 180%. Critical results are reported through parametric illustrations that can be used by designers of prostheses to select optimal components for a prosthetic knee based on the inertial properties of the amputee and his or her prosthetic leg

DefGraspNets: Grasp Planning on 3D Fields with Graph Neural Nets

Robotic grasping of 3D deformable objects is critical for real-world applications such as food handling and robotic surgery. Unlike rigid and articulated objects, 3D deformable objects have infinite degrees of freedom. Fully defining their state requires 3D deformation and stress fields, which are exceptionally difficult to analytically compute or experimentally measure. Thus, evaluating grasp candidates for grasp planning typically requires accurate, but slow 3D finite element method (FEM) simulation. Sampling-based grasp planning is often impractical, as it requires evaluation of a large number of grasp candidates. Gradient-based grasp planning can be more efficient, but requires a differentiable model to synthesize optimal grasps from initial candidates. Differentiable FEM simulators may fill this role, but are typically no faster than standard FEM. In this work, we propose learning a predictive graph neural network (GNN), DefGraspNets, to act as our differentiable model. We train DefGraspNets to predict 3D stress and deformation fields based on FEM-based grasp simulations. DefGraspNets not only runs up to 1500 times faster than the FEM simulator, but also enables fast gradient-based grasp optimization over 3D stress and deformation metrics. We design DefGraspNets to align with real-world grasp planning practices and demonstrate generalization across multiple test sets, including real-world experiments.Comment: To be published in the IEEE Conference on Robotics and Automation (ICRA), 202

MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations

Imitation learning from a large set of human demonstrations has proved to be an effective paradigm for building capable robot agents. However, the demonstrations can be extremely costly and time-consuming to collect. We introduce MimicGen, a system for automatically synthesizing large-scale, rich datasets from only a small number of human demonstrations by adapting them to new contexts. We use MimicGen to generate over 50K demonstrations across 18 tasks with diverse scene configurations, object instances, and robot arms from just ~200 human demonstrations. We show that robot agents can be effectively trained on this generated dataset by imitation learning to achieve strong performance in long-horizon and high-precision tasks, such as multi-part assembly and coffee preparation, across broad initial state distributions. We further demonstrate that the effectiveness and utility of MimicGen data compare favorably to collecting additional human demonstrations, making it a powerful and economical approach towards scaling up robot learning. Datasets, simulation environments, videos, and more at https://mimicgen.github.io .Comment: Conference on Robot Learning (CoRL) 202